Statistical Significance of Precisely Repeated Intracellular Synaptic Patterns

Can neuronal networks produce patterns of activity with millisecond accuracy? It may seem unlikely, considering the probabilistic nature of synaptic transmission. However, some theories of brain function predict that such precision is feasible and can emerge from the non-linearity of the action potential generation in circuits of connected neurons. Several studies have presented evidence for and against this hypothesis. Our earlier work supported the precision hypothesis, based on results demonstrating that precise patterns of synaptic inputs could be found in intracellular recordings from neurons in brain slices and in vivo. To test this hypothesis, we devised a method for finding precise repeats of activity and compared repeats found in the data to those found in surrogate datasets made by shuffling the original data. Because more repeats were found in the original data than in the surrogate data sets, we argued that repeats were not due to chance occurrence. Mokeichev et al. (2007) challenged these conclusions, arguing that the generation of surrogate data was insufficiently rigorous. We have now reanalyzed our previous data with the methods introduced from Mokeichev et al. (2007). Our reanalysis reveals that repeats are statistically significant, thus supporting our earlier conclusions, while also supporting many conclusions that Mokeichev et al. (2007) drew from their recent in vivo recordings. Moreover, we also show that the conditions under which the membrane potential is recorded contributes significantly to the ability to detect repeats and may explain conflicting results. In conclusion, our reevaluation resolves the methodological contradictions between Ikegaya et al. (2004) and Mokeichev et al. (2007), but demonstrates the validity of our previous conclusion that spontaneous network activity is non-randomly organized

Dendritic Slow Dynamics Enables Localized Cortical Activity to Switch between Mobile and Immobile Modes with Noisy Background Input

Mounting lines of evidence suggest the significant computational ability of a single neuron empowered by active dendritic dynamics. This motivates us to study what functionality can be acquired by a network of such neurons. The present paper studies how such rich single-neuron dendritic dynamics affects the network dynamics, a question which has scarcely been specifically studied to date. We simulate neurons with active dendrites networked locally like cortical pyramidal neurons, and find that naturally arising localized activity – called a bump – can be in two distinct modes, mobile or immobile. The mode can be switched back and forth by transient input to the cortical network. Interestingly, this functionality arises only if each neuron is equipped with the observed slow dendritic dynamics and with in vivo-like noisy background input. If the bump activity is considered to indicate a point of attention in the sensory areas or to indicate a representation of memory in the storage areas of the cortex, this would imply that the flexible mode switching would be of great potential use for the brain as an information processing device. We derive these conclusions using a natural extension of the conventional field model, which is defined by combining two distinct fields, one representing the somatic population and the other representing the dendritic population. With this tool, we analyze the spatial distribution of the degree of after-spike adaptation and explain how we can understand the presence of the two distinct modes and switching between the modes. We also discuss the possible functional impact of this mode-switching ability

Expression of methylation-related genes is associated with overall survival in patients with non-small cell lung cancer

The abnormality of DNA methylation is involved in tumour progression, and thus has a modulating effect on clinical outcome of cancer patients. In this study, we measured the mRNA expression levels of three methylation-regulating genes (DNMT1, DNMT3b, and MBD2) in 148 tumour samples from patients with non-small cell lung cancer (NSCLC) using quantitative real-time polymerase chain reaction and then determined their prognostic values. Our data showed that the high level of DNMT1 expression was significantly associated with an increased risk of death in all NSCLC patients (hazard ratio (HR), 1.74; 95% confidence interval (95% CI), 1.04–2.90). However, the high level of DNMT3b expression was significantly associated with poor prognosis only in young patients (<65 years). The high level of MBD2 expression had a significantly reduced risk for death only in male patients and in squamous cell lung carcinoma (SQLC) patients. All three combination groups with DNMT1 and DNMT3b, DNMT1 and MBD2 or DNMT3b and MBD2 revealed significant combined effects in male patients and SQLC patients. Our results suggest that DNMT1, DNMT3b, and MBD2 may play important roles in modulating NSCLC patient survival and thus be useful for identifying NSCLC patients who would benefit most from aggressive therapy

Decreased expression of 17β-hydroxysteroid dehydrogenase type 1 is associated with DNA hypermethylation in colorectal cancer located in the proximal colon

<p>Abstract</p> <p>Background</p> <p>The importance of 17β-estradiol (E2) in the prevention of large bowel tumorigenesis has been shown in many epidemiological studies. Extragonadal E2 may form by the aromatase pathway from androstenedione or the sulfatase pathway from estrone (E1) sulfate followed by E1 reduction to E2 by 17-β-hydroxysteroid dehydrogenase (HSD17B1), so <it>HSD17B1 </it>gene expression may play an important role in the production of E2 in peripheral tissue, including the colon.</p> <p>Methods</p> <p><it>HSD17B1 </it>expression was analyzed in colorectal cancer cell lines (HT29, SW707) and primary colonic adenocarcinoma tissues collected from fifty two patients who underwent radical colon surgical resection. Histopathologically unchanged colonic mucosa located at least 10-20 cm away from the cancerous lesions was obtained from the same patients. Expression level of <it>HSD17B1 </it>using quantitative PCR and western blot were evaluated. DNA methylation level in the 5' flanking region of <it>HSD17B1 </it>CpG rich region was assessed using bisulfite DNA sequencing and HRM analysis. The influence of DNA methylation on HSD17B1 expression was further evaluated by ChIP analysis in HT29 and SW707 cell lines. The conversion of estrone (E1) in to E2 was determined by electrochemiluminescence method.</p> <p>Results</p> <p>We found a significant decrease in HSD17B1 transcript (<it>p </it>= 0.0016) and protein (<it>p </it>= 0.0028) levels in colorectal cancer (CRC) from the proximal but not distal colon and rectum. This reduced <it>HSD17B1 </it>expression was associated with significantly increased DNA methylation (<it>p </it>= 0.003) in the CpG rich region located in the 5' flanking sequence of the <it>HSD17B1 </it>gene in CRC in the proximal but not distal colon and rectum. We also showed that 5-dAzaC induced demethylation of the 5' flanking region of <it>HSD17B1</it>, leading to increased occupation of the promoter by Polymerase II, and increased transcript and protein levels in HT29 and SW707 CRC cells, which contributed to the increase in E2 formation.</p> <p>Conclusions</p> <p>Our results showed that reduced <it>HSD17B1 </it>expression can be associated with DNA methylation in the 5' flanking region of <it>HSD17B1 </it>in CRC from the proximal colon.</p

Clinicopathological Significance and Prognostic Value of DNA Methyltransferase 1, 3a, and 3b Expressions in Sporadic Epithelial Ovarian Cancer

Altered DNA methylation of tumor suppressor gene promoters plays a role in human carcinogenesis and DNA methyltransferases (DNMTs) are responsible for it. This study aimed to determine aberrant expression of DNMT1, DNMT3a, and DNMT3b in benign and malignant ovarian tumor tissues for their association with clinicopathological significance and prognostic value. A total of 142 ovarian cancers and 44 benign ovarian tumors were recruited for immunohistochemical analysis of their expression. The data showed that expression of DNMT1, DNMT3a, and DNMT3b was observed in 76 (53.5%), 92 (64.8%) and 79 (55.6%) of 142 cases of ovarian cancer tissues, respectively. Of the serious tumors, DNMT3a protein expression was significantly higher than that in benign tumor samples (P = 0.001); DNMT3b was marginally significant down regulated in ovarian cancers compared to that of the benign tumors (P = 0.054); DNMT1 expression has no statistical difference between ovarian cancers and benign tumor tissues (P = 0.837). Of the mucious tumors, the expression of DNMT3a, DNMT3b, and DNMT1 was not different between malignant and benign tumors. Moreover, DNMT1 expression was associated with DNMT3b expression (P = 0.020, r = 0.195). DNMT1 expression was associated with age of the patients, menopause status, and tumor localization, while DNMT3a expression was associated with histological types and serum CA125 levels and DNMT3b expression was associated with lymph node metastasis. In addition, patients with DNMT1 or DNMT3b expression had a trend of better survival than those with negative expression. Co-expression of DNMT1 and DNMT3b was significantly associated with better overall survival (P = 0.014). The data from this study provided the first evidence for differential expression of DNMTs proteins in ovarian cancer tissues and their associations with clinicopathological and survival data in sporadic ovarian cancer patients

History-Dependent Excitability as a Single-Cell Substrate of Transient Memory for Information Discrimination

Neurons react differently to incoming stimuli depending upon their previous history of stimulation. This property can be considered as a single-cell substrate for transient memory, or context-dependent information processing: depending upon the current context that the neuron “sees” through the subset of the network impinging on it in the immediate past, the same synaptic event can evoke a postsynaptic spike or just a subthreshold depolarization. We propose a formal definition of History-Dependent Excitability (HDE) as a measure of the propensity to firing in any moment in time, linking the subthreshold history-dependent dynamics with spike generation. This definition allows the quantitative assessment of the intrinsic memory for different single-neuron dynamics and input statistics. We illustrate the concept of HDE by considering two general dynamical mechanisms: the passive behavior of an Integrate and Fire (IF) neuron, and the inductive behavior of a Generalized Integrate and Fire (GIF) neuron with subthreshold damped oscillations. This framework allows us to characterize the sensitivity of different model neurons to the detailed temporal structure of incoming stimuli. While a neuron with intrinsic oscillations discriminates equally well between input trains with the same or different frequency, a passive neuron discriminates better between inputs with different frequencies. This suggests that passive neurons are better suited to rate-based computation, while neurons with subthreshold oscillations are advantageous in a temporal coding scheme. We also address the influence of intrinsic properties in single-cell processing as a function of input statistics, and show that intrinsic oscillations enhance discrimination sensitivity at high input rates. Finally, we discuss how the recognition of these cell-specific discrimination properties might further our understanding of neuronal network computations and their relationships to the distribution and functional connectivity of different neuronal types

Histone deacetylases in viral infections

Chromatin remodeling and gene expression are regulated by histone deacetylases (HDACs) that condense the chromatin structure by deacetylating histones. HDACs comprise a group of enzymes that are responsible for the regulation of both cellular and viral genes at the transcriptional level. In mammals, a total of 18 HDACs have been identified and grouped into four classes, i.e., class I (HDACs 1, 2, 3, 8), class II (HDACs 4, 5, 6, 7, 9, 10), class III (Sirt1–Sirt7), and class IV (HDAC11). We review here the role of HDACs on viral replication and how HDAC inhibitors could potentially be used as new therapeutic tools in several viral infections